Inference of genomic landscapes using ordered Hidden Markov Models with emission densities (oHMMed).

BACKGROUND: Genomes are inherently inhomogeneous, with features such as base composition, recombination, gene density, and gene expression varying along chromosomes. Evolutionary, biological, and biomedical analyses aim to quantify this variation, account for it during inference procedures, and ultimately determine the causal processes behind it. Since sequential observations along chromosomes are not independent, it is unsurprising that autocorrelation patterns have been observed e.g., in human base composition. In this article, we develop a class of Hidden Markov Models (HMMs) called oHMMed (ordered HMM with emission densities, the corresponding R package of the same name is available on CRAN): They identify the number of comparably homogeneous regions within autocorrelated observed sequences. These are modelled as discrete hidden states; the observed data points are realisations of continuous probability distributions with state-specific means that enable ordering of these distributions. The observed sequence is labelled according to the hidden states, permitting only neighbouring states that are also neighbours within the ordering of their associated distributions. The parameters that characterise these state-specific distributions are inferred. RESULTS: We apply our oHMMed algorithms to the proportion of G and C bases (modelled as a mixture of normal distributions) and the number of genes (modelled as a mixture of poisson-gamma distributions) in windows along the human, mouse, and fruit fly genomes. This results in a partitioning of the genomes into regions by statistically distinguishable averages of these features, and in a characterisation of their continuous patterns of variation. In regard to the genomic G and C proportion, this latter result distinguishes oHMMed from segmentation algorithms based in isochore or compositional domain theory. We further use oHMMed to conduct a detailed analysis of variation of chromatin accessibility (ATAC-seq) and epigenetic markers H3K27ac and H3K27me3 (modelled as a mixture of poisson-gamma distributions) along the human chromosome 1 and their correlations. CONCLUSIONS: Our algorithms provide a biologically assumption free approach to characterising genomic landscapes shaped by continuous, autocorrelated patterns of variation. Despite this, the resulting genome segmentation enables extraction of compositionally distinct regions for further downstream analyses.

Transcriptomic profiling of different developmental stages reveals parasitic strategies of Wohlfahrtia magnifica, a myiasis-causing flesh fly.

BACKGROUND: Wohlfahrtia magnifica is an obligatory parasite that causes myiasis in several warm-blooded vertebrates. Adult females deposit the first-stage larvae directly onto wounds or natural body orifices (e.g., genitalia) of the host, from where they quickly colonize the host tissue and feed on it for development. The infestation of W. magnifica can lead to health issues, welfare concerns, and substantial economic losses. To date, little is known about the molecular mechanisms of the W. magnifica-causing myiasis. RESULTS: In this study, we collected parasitic-stage larvae of W. magnifica from wounds of naturally infested Bactrian camels, as well as pupae and adult flies reared in vitro from the wound-collected larvae, for investigating the gene expression profiles of the different developmental stages of W. magnifica, with a particular focus on examining gene families closely related to the parasitism of the wound-collected larvae. As key proteins related to the parasite-host interaction, 2049 excretory/secretory (ES) proteins were identified in W. magnifica through the integration of multiple bioinformatics approaches. Functional analysis indicates that these ES proteins are primarily involved in cuticle development, peptidase activity, immune response, and metabolic processes. The global investigation of gene expression at different developmental stages using pairwise comparisons and weighted correlation network analysis (WGCNA) showed that the upregulated genes during second-stage larvae were related to cuticle development, peptidase activity, and RNA transcription and translation; during third-stage larvae to peptidase inhibitor activity and nutrient reservoir activity; during pupae to cell and tissue morphogenesis and cell and tissue development; and during adult flies to signal perception, many of them involved in light perception, and adult behavior, e.g., feeding, mating, and locomotion. Specifically, the expression level analysis of the likely parasitism-related genes in parasitic wound-collected larvae revealed a significant upregulation of 88 peptidase genes (including 47 serine peptidase genes), 110 cuticle protein genes, and 21 heat shock protein (hsp) genes. Interestingly, the expression of 2 antimicrobial peptide (AMP) genes, including 1 defensin and 1 diptericin, was also upregulated in the parasitic larvae. CONCLUSIONS: We identified ES proteins in W. magnifica and investigated their functional distribution. In addition, gene expression profiles at different developmental stages of W. magnifica were examined. Specifically, we focused on gene families closely related to parasitism of wound-collected larvae. These findings shed light on the molecular mechanisms underlying the life cycle of the myiasis-causing fly, especially during the parasitic larval stages, and provide guidance for the development of control measures against W. magnifica.

The expected sample allele frequencies from populations of changing size via orthogonal polynomials.

In this article, discrete and stochastic changes in (effective) population size are incorporated into the spectral representation of a biallelic diffusion process for drift and small mutation rates. A forward algorithm inspired by Hidden-Markov-Model (HMM) literature is used to compute exact sample allele frequency spectra for three demographic scenarios: single changes in (effective) population size, boom-bust dynamics, and stochastic fluctuations in (effective) population size. An approach for fully agnostic demographic inference from these sample allele spectra is explored, and sufficient statistics for stepwise changes in population size are found. Further, convergence behaviours of the polymorphic sample spectra for population size changes on different time scales are examined and discussed within the context of inference of the effective population size. Joint visual assessment of the sample spectra and the temporal coefficients of the spectral decomposition of the forward diffusion process is found to be important in determining departure from equilibrium. Stochastic changes in (effective) population size are shown to shape sample spectra particularly strongly.

The influence of GC-biased gene conversion on non-adaptive sequence evolution in short introns of Drosophila melanogaster.

Population genetic inference of selection on the nucleotide sequence level often proceeds by comparison to a reference sequence evolving only under mutation and population demography. Among the few candidates for such a reference sequence is the 5' part of short introns (5SI) in Drosophila. In addition to mutation and population demography, however, there is evidence for a weak force favouring GC bases, likely due to GC-biased gene conversion (gBGC), and for the effect of linked selection. Here, we use polymorphism and divergence data of Drosophila melanogaster to detect and describe the forces affecting the evolution of the 5SI. We separately analyse mutation classes, compare them between chromosomes, and relate them to recombination rate frequencies. GC-conservative mutations seem to be mainly influenced by mutation and drift, with linked selection mostly causing differences between the central and the peripheral (i.e., telomeric and centromeric) regions of the chromosome arms. Comparing GC-conservative mutation patterns between autosomes and the X chromosome showed differences in mutation rates, rather than linked selection, in the central chromosomal regions after accounting for differences in effective population sizes. On the other hand, GC-changing mutations show asymmetric site frequency spectra, indicating the presence of gBGC, varying among mutation classes and in intensity along chromosomes, but approximately equal in strength in autosomes and the X chromosome.

Drivers of genomic landscapes of differentiation across a Populus divergence gradient.

Speciation, the continuous process by which new species form, is often investigated by looking at the variation of nucleotide diversity and differentiation across the genome (hereafter genomic landscapes). A key challenge lies in how to determine the main evolutionary forces at play shaping these patterns. One promising strategy, albeit little used to date, is to comparatively investigate these genomic landscapes as progression through time by using a series of species pairs along a divergence gradient. Here, we resequenced 201 whole-genomes from eight closely related Populus species, with pairs of species at different stages along the divergence gradient to learn more about speciation processes. Using population structure and ancestry analyses, we document extensive introgression between some species pairs, especially those with parapatric distributions. We further investigate genomic landscapes, focusing on within-species (i.e. nucleotide diversity and recombination rate) and among-species (i.e. relative and absolute divergence) summary statistics of diversity and divergence. We observe relatively conserved patterns of genomic divergence across species pairs. Independent of the stage across the divergence gradient, we find support for signatures of linked selection (i.e. the interaction between natural selection and genetic linkage) in shaping these genomic landscapes, along with gene flow and standing genetic variation. We highlight the importance of investigating genomic patterns on multiple species across a divergence gradient and discuss prospects to better understand the evolutionary forces shaping the genomic landscapes of diversity and differentiation.

Oncogenic TYK2 P760L kinase is effectively targeted by combinatorial TYK2, mTOR and CDK4/6 kinase blockade.

Tyrosine kinase 2 (TYK2) is a member of the Janus kinase/signal transducer and activator of transcription pathway, which is central in cytokine signaling. Previously, germline TYK2 mutations have been described in two patients developing de novo T-cell acute lymphoblastic leukemias (T-ALL) or precursor B-ALL. The mutations (P760L and G761V) are located within the regulatory pseudokinase domain and lead to constitutive activation of TYK2. We demonstrate the transformation capacity of TYK2 P760L in hematopoietic cell systems including primary bone marrow cells. In vivo engraftment of TYK2 P760L-expressing cell lines led to development of leukemia. A kinase inhibitor screen uncovered that oncogenic TYK2 acts synergistically with the PI3K/AKT/mTOR and CDK4/6 pathways. Accordingly, the TYK2-specific inhibitor deucravacitinib (BMS986165) reduces cell viability of TYK2 P760L-transformed cell models and ex vivo cultured TYK2 P760L-mutated patient- derived xenograft cells most efficiently when combined with mTOR or CDK4/6 inhibitors. Our study thereby pioneers novel treatment options for patients suffering from TYK2-driven acute leukemia.

Purifying selection against spurious splicing signals contributes to the base composition evolution of the polypyrimidine tract.

Among eukaryotes, the major spliceosomal pathway is highly conserved. While long introns may contain additional regulatory sequences, the ones in short introns seem to be nearly exclusively related to splicing. Although these regulatory sequences involved in splicing are well-characterized, little is known about their evolution. At the 3' end of introns, the splice signal nearly universally contains the dimer AG, which consists of purines, and the polypyrimidine tract upstream of this 3' splice signal is characterized by over-representation of pyrimidines. If the over-representation of pyrimidines in the polypyrimidine tract is also due to avoidance of a premature splicing signal, we hypothesize that AG should be the most under-represented dimer. Through the use of DNA-strand asymmetry patterns, we confirm this prediction in fruit flies of the genus Drosophila and by comparing the asymmetry patterns to a presumably neutrally evolving region, we quantify the selection strength acting on each motif. Moreover, our inference and simulation method revealed that the best explanation for the base composition evolution of the polypyrimidine tract is the joint action of purifying selection against a spurious 3' splice signal and the selection for pyrimidines. Patterns of asymmetry in other eukaryotes indicate that avoidance of premature splicing similarly affects the nucleotide composition in their polypyrimidine tracts.

Sedative effects and changes in cardiac rhythm with intravenous premedication of medetomidine, butorphanol and ketamine in dogs.

OBJECTIVE: To determine the sedative effects and characteristics of cardiac rhythm with intravenous (IV) premedication of medetomidine, butorphanol and ketamine in dogs. STUDY DESIGN: Prospective, blinded, randomized clinical trial. ANIMALS: A total of 116 client-owned healthy dogs undergoing elective surgery. METHODS: Dogs were randomly allocated one of four groups: group M, medetomidine 5 µg kg-1; group B, butorphanol 0.2 mg kg-1; group MB, medetomidine 5 µg kg-1 and butorphanol 0.2 mg kg-1; or group MBK, medetomidine 5 µg kg-1, butorphanol 0.2 mg kg-1 and ketamine 1 mg kg-1 IV. Sedation was assessed using a numerical descriptive scale. Heart rate (HR) and rhythm were monitored; propofol dose (mg kg-1 IV) to allow orotracheal intubation was documented. Data were analysed using anova, accounting for multiple testing with the Tukey honest significant difference test. RESULTS: Sedation scores varied significantly between all groups at all time points, except between groups MB and MBK at four time points. HR decreased in all groups: most in groups M and MB, least in group B. HR was initially higher in group MBK than in groups M and MB. Arrhythmias occurred in all groups: group B showed second-degree atrioventricular blocks occasionally, all other groups showed additionally ventricular escape complexes and bundle branch blocks. Dose of propofol required for orotracheal intubation was significantly higher in group B (5.0 ± 2.0 mg kg-1) than in group M (2.6 ± 0.6 mg kg-1). Although no difference could be demonstrated between groups MB (1.4 ± 0.6 mg kg-1) and MBK (0.9 ± 0.8 mg kg-1), both groups required significantly less propofol than group M. CONCLUSION AND CLINICAL RELEVANCE: Medetomidine-based premedication protocols led to various bradyarrhythmias. Addition of subanaesthetic doses of ketamine to medetomidine-based protocols resulted in higher HRs, fewer bradyarrhythmias and fewer animals that required propofol for intubation without causing side effects in healthy dogs.

A nearly-neutral biallelic Moran model with biased mutation and linear and quadratic selection.

In this article, a biallelic reversible mutation model with linear and quadratic selection is analysed. The approach reconnects to one proposed by Kimura (1979), who starts from a diffusion model and derives its equilibrium distribution up to a constant. We use a boundary-mutation Moran model, which approximates a general mutation model for small effective mutation rates, and derive its equilibrium distribution for polymorphic and monomorphic variants in small to moderately sized populations. Using this model, we show that biased mutation rates and linear selection alone can cause patterns of polymorphism within and substitution rates between populations that are usually ascribed to balancing or overdominant selection. We illustrate this using a data set of short introns and fourfold degenerate sites from Drosophila simulans and Drosophila melanogaster.

Maximum likelihood estimators for scaled mutation rates in an equilibrium mutation-drift model.

The stationary sampling distribution of a neutral decoupled Moran or Wright-Fisher diffusion with neutral mutations is known to first order for a general rate matrix with small but otherwise unconstrained mutation rates. Using this distribution as a starting point we derive results for maximum likelihood estimates of scaled mutation rates from site frequency data under three model assumptions: a twelve-parameter general rate matrix, a nine-parameter reversible rate matrix, and a six-parameter strand-symmetric rate matrix. The site frequency spectrum is assumed to be sampled from a fixed size population in equilibrium, and to consist of allele frequency data at a large number of unlinked sites evolving with a common mutation rate matrix without selective bias. We correct an error in a previous treatment of the same problem (Burden and Tang, 2017) affecting the estimators for the general and strand-symmetric rate matrices. The method is applied to a biological dataset consisting of a site frequency spectrum extracted from short autosomal introns in a sample of Drosophila melanogaster individuals.

Identification of Rabbit Oviductal Fluid Proteins Involved in Pre-Fertilization Processes by Quantitative Proteomics.

Oviductal fluid (ODF) proteins modulate and support reproductive processes in the oviduct. In the present study, proteins involved in the biological events that precede fertilization have been identified in the rabbit ODF proteome, isolated from the ampulla and isthmus of the oviduct at different time points within 8 h after intrauterine insemination. A workflow is used that integrates lectin affinity capture with stable-isotope dimethyl labeling prior to nanoLC-MS/MS analysis. In total, over 400 ODF proteins, including 214 lectin enriched glycoproteins, are identified and quantified. Selected data are validated by Western blot analysis. Spatiotemporal alterations in the abundance of ODF proteins in response to insemination are detected by global analysis. A subset of 63 potentially biologically relevant ODF proteins is identified, including extracellular matrix components, chaperones, oxidoreductases, and immunity proteins. Functional enrichment analysis reveals an altered peptidase regulator activity upon insemination. In addition to protein identification and abundance changes, N-glycopeptide analysis further identifies 281 glycosites on 199 proteins. Taken together, these results show, for the first time, the evolving oviductal milieu early upon insemination. The identified proteins are likely those that modulate in vitro processes, including spermatozoa function.

Nonconventional initiation complex assembly by STAT and NF-kappaB transcription factors regulates nitric oxide synthase expression.

Transcriptional regulation of the Nos2 gene encoding inducible nitric oxide synthase (iNOS) requires type I interferon (IFN-I) signaling and additional signals emanating from pattern recognition receptors. Here we showed sequential and cooperative contributions of the transcription factors ISGF3 (a complex containing STAT1, STAT2, and IRF9 subunits) and NF-kappaB to the transcriptional induction of the Nos2 gene in macrophages infected with the intracellular bacterial pathogen Listeria monocytogenes. NF-kappaB preceded ISGF3 at the Nos2 promoter and generated a transcriptional memory effect by depositing basal transcription factor TFIIH with the associated CDK7 kinase for serine 5 phosphorylation of the RNA polymerase II (pol II) carboxyterminal domain (CTD). Subsequent to TFIIH deposition by NF-kappaB, ISGF3 attracted the pol II enzyme and phosphorylation at CTD S5 occurred. Thus, STATs and NF-kappaB cooperate through pol II promoter recruitment and the phosphorylation of its CTD, respectively, as a prerequisite for productive elongation of iNOS mRNA.

Canine mammary tumour cells exposure to sevoflurane: effects on cell proliferation and neuroepithelial transforming gene 1 expression.

OBJECTIVE: The influence of perioperative factors, such as anaesthetic and analgesic techniques, on metastatic spread following surgery for primary cancer removal is of growing interest. The present study investigated the effects of sevoflurane on canine mammary tumour cell proliferation (MTT colorimetric assay) and on the expression of neuroepithelial transforming gene 1 (NET1). STUDY DESIGN: Prospective controlled in vitro trial. STUDY MATERIAL: Primary (CIPp) and metastatic canine tubular adenocarcinoma (CIPm) cells. METHODS: To perform MTT tests, cell lines were seeded at a density of 3000 cells per well and incubated with sevoflurane (1, 2.5 or 4 mM) or only with the culture medium (control). Sevoflurane was added to the cell cultures every hour to avoid changes in drug concentration. MTT assays were performed after 6 hours of exposure obtaining absolute values of absorbance. The RNA isolated from the lysates of the same cell lines underwent quantitative polymerase chain reaction to evaluate NET1 gene expression changes compared with controls. One- or two-way analysis of variance was used as appropriate (p < 0.05). RESULTS: A significant increase in cell proliferation compared with controls was observed in CIPp treated with lower sevoflurane concentrations, whereas a significant decrease in cell proliferation was found in CIPm treated with all the sevoflurane concentrations. All CIPp treatments did not induce changes in gene expression compared with controls, whereas a significant increase in gene expression was observed in CIPm between controls and the higher sevoflurane concentration. CONCLUSIONS AND CLINICAL RELEVANCE: Sevoflurane treatments modified the cell proliferation rate in both cell lines showing an increase or decrease when applied to CIPp or CIPm, respectively. Expression of the NET1 gene increased after treatment with sevoflurane 4 mM in metastatic cells. The role of sevoflurane on cancer recurrence should be further investigated.

Inference in population genetics using forward and backward, discrete and continuous time processes.

A central aim of population genetics is the inference of the evolutionary history of a population. To this end, the underlying process can be represented by a model of the evolution of allele frequencies parametrized by e.g., the population size, mutation rates and selection coefficients. A large class of models use forward-in-time models, such as the discrete Wright-Fisher and Moran models and the continuous forward diffusion, to obtain distributions of population allele frequencies, conditional on an ancestral initial allele frequency distribution. Backward-in-time diffusion processes have been rarely used in the context of parameter inference. Here, we demonstrate how forward and backward diffusion processes can be combined to efficiently calculate the exact joint probability distribution of sample and population allele frequencies at all times in the past, for both discrete and continuous population genetics models. This procedure is analogous to the forward-backward algorithm of hidden Markov models. While the efficiency of discrete models is limited by the population size, for continuous models it suffices to expand the transition density in orthogonal polynomials of the order of the sample size to infer marginal likelihoods of population genetic parameters. Additionally, conditional allele trajectories and marginal likelihoods of samples from single populations or from multiple populations that split in the past can be obtained. The described approaches allow for efficient maximum likelihood inference of population genetic parameters in a wide variety of demographic scenarios.

Response to interferons and antibacterial innate immunity in the absence of tyrosine-phosphorylated STAT1.

Signal transducer and activator of transcription 1 (STAT1) plays a pivotal role in the innate immune system by directing the transcriptional response to interferons (IFNs). STAT1 is activated by Janus kinase (JAK)-mediated phosphorylation of Y701. To determine whether STAT1 contributes to cellular responses without this phosphorylation event, we generated mice with Y701 mutated to a phenylalanine (Stat1(Y701F)). We show that heterozygous mice do not exhibit a dominant-negative phenotype. Homozygous Stat1(Y701F) mice show a profound reduction in Stat1 expression, highlighting an important role for basal IFN-dependent signaling. The rapid transcriptional response to type I IFN (IFN-I) and type II IFN (IFNγ) was absent in Stat1(Y701F) cells. Intriguingly, STAT1Y701F suppresses the delayed expression of IFN-I-stimulated genes (ISG) observed in Stat1(-/-) cells, mediated by the STAT2/IRF9 complex. Thus, Stat1(Y701F) macrophages are more susceptible to Legionella pneumophila infection than Stat1(-/-) macrophages. Listeria monocytogenes grew less robustly in Stat1(Y701F) macrophages and mice compared to Stat1(-/-) counterparts, but STAT1Y701F is not sufficient to rescue the animals. Our studies are consistent with a potential contribution of Y701-unphosphorylated STAT1 to innate antibacterial immunity.

Tristetraprolin binding site atlas in the macrophage transcriptome reveals a switch for inflammation resolution.

Precise regulation of mRNA decay is fundamental for robust yet not exaggerated inflammatory responses to pathogens. However, a global model integrating regulation and functional consequences of inflammation-associated mRNA decay remains to be established. Using time-resolved high-resolution RNA binding analysis of the mRNA-destabilizing protein tristetraprolin (TTP), an inflammation-limiting factor, we qualitatively and quantitatively characterize TTP binding positions in the transcriptome of immunostimulated macrophages. We identify pervasive destabilizing and non-destabilizing TTP binding, including a robust intronic binding, showing that TTP binding is not sufficient for mRNA destabilization. A low degree of flanking RNA structuredness distinguishes occupied from silent binding motifs. By functionally relating TTP binding sites to mRNA stability and levels, we identify a TTP-controlled switch for the transition from inflammatory into the resolution phase of the macrophage immune response. Mapping of binding positions of the mRNA-stabilizing protein HuR reveals little target and functional overlap with TTP, implying a limited co-regulation of inflammatory mRNA decay by these proteins. Our study establishes a functionally annotated and navigable transcriptome-wide atlas (http://ttp-atlas.univie.ac.at) of cis-acting elements controlling mRNA decay in inflammation.

High-throughput mRNA and miRNA profiling of epithelial-mesenchymal transition in MDCK cells.

BACKGROUND: Epithelial-mesenchymal transition (EMT) is an important process in embryonic development, especially during gastrulation and organ formation. Furthermore EMT is widely observed in pathological conditions, e.g., fibrosis, tumor progression and metastasis. Madin-Darby Canine Kidney (MDCK) cells are widely used for studies of EMT and epithelial plasticity. MDCK cells show an epithelial phenotype, while oncogenic Ras-transformed MDCK (MDCK-Ras) cells undergo EMT and show a mesenchymal phenotype. METHODS: RNA-Seq and miRNA-Seq analyses were performed on MDCK and MDCK-Ras cells. Data were validated by qRT-PCR. Gene signature analyses were carried out to identify pathways and gene ontology terms. For selected miRNAs target prediction was performed. RESULTS: With RNA-Seq, mRNAs of approximately half of the genes known for dog were detected. These were screened for differential regulation during Ras-induced EMT. We went further and performed gene signature analyses and found Gene Ontology (GO) terms and pathways important for epithelial polarity and implicated in EMT. Among the identified pathways, TGFß1 emerged as a central signaling factor in many EMT related pathways and biological processes. With miRNA-Seq, approximately half of the known canine miRNAs were found expressed in MDCK and MDCK-Ras cells. Furthermore, among differentially expressed miRNAs, miRNAs that are known to be important regulators of EMT were detected and new candidates were predicted. New dog miRNAs were discovered after aligning our reads to that of other species in miRBase. Importantly, we could identify 25 completely novel miRNAs with a stable hairpin structure. Two of these novel miRNAs were differentially expressed. We validated the two novel miRNAs with the highest read counts by RT-qPCR. Target prediction of a particular novel miRNA highly expressed in mesenchymal MDCK-Ras cells revealed that it targets components of epithelial cell junctional complexes. Combining target prediction for the most upregulated miRNAs and validation of the targets in MDCK-Ras cells with pathway analysis allowed us to identify two novel pathways, e.g., JAK/STAT signaling and pancreatic cancer pathways. These pathways could not be detected solely by gene set enrichment analyses of RNA-Seq data. CONCLUSION: With deep sequencing data of mRNAs and miRNAs of MDCK cells and of Ras-induced EMT in MDCK cells, differentially regulated mRNAs and miRNAs are identified. Many of the identified genes are within pathways known to be involved in EMT. Novel differentially upregulated genes in MDCK cells are interferon stimulated genes and genes involved in Slit and Netrin signaling. New pathways not yet linked to these processes were identified. A central pathway in Ras induced EMT is TGFß signaling, which leads to differential regulation of many target genes, including miRNAs. With miRNA-Seq we identified miRNAs involved in either epithelial cell biology or EMT. Finally, we describe completely novel miRNAs and their target genes.

Inference of directional selection and mutation parameters assuming equilibrium.

In a classical study, Wright (1931) proposed a model for the evolution of a biallelic locus under the influence of mutation, directional selection and drift. He derived the equilibrium distribution of the allelic proportion conditional on the scaled mutation rate, the mutation bias and the scaled strength of directional selection. The equilibrium distribution can be used for inference of these parameters with genome-wide datasets of "site frequency spectra" (SFS). Assuming that the scaled mutation rate is low, Wright's model can be approximated by a boundary-mutation model, where mutations are introduced into the population exclusively from sites fixed for the preferred or unpreferred allelic states. With the boundary-mutation model, inference can be partitioned: (i) the shape of the SFS distribution within the polymorphic region is determined by random drift and directional selection, but not by the mutation parameters, such that inference of the selection parameter relies exclusively on the polymorphic sites in the SFS; (ii) the mutation parameters can be inferred from the amount of polymorphic and monomorphic preferred and unpreferred alleles, conditional on the selection parameter. Herein, we derive maximum likelihood estimators for the mutation and selection parameters in equilibrium and apply the method to simulated SFS data as well as empirical data from a Madagascar population of Drosophila simulans.

Estimating the scaled mutation rate and mutation bias with site frequency data.

The distribution of allele frequencies of a large number of biallelic sites is known as "allele-frequency spectrum" or "site-frequency spectrum" (SFS). Without selection and in regions of relatively high recombination rates, sites may be assumed to be independently and identically distributed. With a beta equilibrium distribution of allelic proportions and binomial sampling, a beta-binomial compound likelihood for each site results. The likelihood of the data and the posterior distribution of two parameters, scaled mutation rate θ and mutation bias α, is investigated in the general case and for small scaled mutation rates θ. In the general case, an expectation-maximization (EM) algorithm is derived to obtain maximum likelihood estimates of both parameters. With an appropriate prior distribution, a Markov chain Monte Carlo sampler to integrate the posterior distribution is also derived. As far as I am aware, previous maximum likelihood or Bayesian estimators of θ, explicitly or implicitly assume small scaled mutation rates, i.e., θ≪1. For θ≪1, maximum-likelihood estimators are also derived for both parameters using a Taylor series expansion of the beta-binomial distribution. The estimator of θ is a variant of the Ewens-Watterson estimator and of the maximum likelihood estimator derived with the Poisson Random Field approach. With a conjugate prior distribution, marginal and conditional beta posterior distributions are also derived for both parameters.

Which factors influence the outcome of experimental infection with Cystoisospora suis?

For reliable predictions of clinical and parasitological outcome of experimental infections with parasites, different models must be evaluated for possible influences of infection time point, infection dose and host-specific parameters such as breed or litter size. To address these issues for Cystoisospora (syn. Isospora) suis, the causative agent of porcine neonatal coccidiosis, 181 piglets from 90 litters (hybrid crosses of different breeds) were included in a retrospective study to evaluate differences in time point and dose of infection in four different experimental models ((1) 1,500 oocysts on the 4th day of life, d.o.l.; (2) 1,000 oocysts, 4th d.o.l.; (3) 1,000 oocysts, 1st d.o.l.; (4) 5,000 oocysts, 4th d.o.l.). The target variables body weight gain, faecal consistency and oocyst excretion were evaluated during the acute phase of infection (5-10 days post infection), and the influences of the dependent variables breed or litter size were estimated. Despite differences in the time course of excretion and faecal consistency, neither the average amount of excretion nor the average faecal consistency differed among models, breeds or litters of different size. High individual variability was seen in all four models as described earlier for higher infection doses. When infections on the 1st vs. 4th day of life were compared, no differences in averages could be found, in contrast to previous observations on the influence of age. Other, not yet defined, variables appear to have a greater impact on the outcome of infection than doses and time points in the tested range, despite the reliable outcome of infection with high excretion rates and signs of clinical disease.